Direct to digital oximeter and method for calculating oxygenation levels

ABSTRACT

An oximeter for non-invasively measuring the oxygen saturation in blood with increased speed and accuracy is disclosed. The oximeter includes a number of features which increase the functionality of the device including: a dynamic range control for monitoring a range of inputs from low level signals encountered in fetal and other applications to typical or high level signals; light emitting devices of different wavelengths for filtering noise and providing additional medial monitoring functions; and an improved method for calculating the oxygenation levels without the need to take peak and valley measurements. The device includes a sensor unit which can be attached to a patient and an oximeter which determines the oxygen saturation in the blood based on signals received from the sensor. The sensor can include light emitting devices in three or more wavelengths to provide additional functions. In the present invention, the detected signal is immediately converted to a digital value.

[0001] The present invention is concerned generally with an improvedoximeter for non-invasively measuring arterial oxygen saturation. Moreparticularly, this invention is concerned with an improved method fordirect digital signal formation from input signals produced by a sensordevice which is connected to the oximeter.

[0002] In all oximeters, input signals are received from a sensor devicewhich is directly connected to the blood-carrying tissue of a patient,such as a finger or ear lobe. The sensor device generally consists of ared LED, an infrared LED, and one or two photodetectors. Light from eachLED is transmitted through the tissue, and the photodetectors detect theamount of light which passes through the tissue. The detected lightconsists of two components for each bandwidth. An AC componentrepresents the amount of pulsating blood detected, while the DCcomponent represents the amount of non-pulsating blood. Therefore, fourseparate components of detected light are examined in order to determinethe arterial oxygen saturation: red DC, red AC, infrared DC and infraredAC. The amount of light detected is then used to determine the oxygensaturation in the blood of the patient based on the following equation:

(IR(AC)/IR(DC))/(Red(AC)/Red(DC))

[0003] In a traditional oximeter, the sensor output signal is convertedto an analog voltage and then separated into infrared and redcomponents. Some oximeters further separate the AC and DC components.Separate analog circuits are then used to sample, demultiplex, andfilter these signals. In these systems, therefore, it is necessary tocarefully match the analog components to minimize errors which canresult from differences in gain or frequency response in the twocircuits. Furthermore, because of the need to carefully match hardwarefor each analog input circuit, and the increased probability of errorswhen additional analog channels are added, traditional oximeters aregenerally limited to two analog inputs.

[0004] Additionally, the analog circuitry employed in traditionaloximeters is generally insufficient to accurately detect low levelsignals. Therefore, these oximeters are generally ineffective formonitoring fetal conditions, as well as for use with patients with thickor very dark skin. Furthermore, the methods used in prior art oximetersfor measuring oxygenation levels rely heavily on pulse detection andpeak-valley measurements which are highly susceptible to variations dueto motion artifact noise.

[0005] The instant invention improves on the analog signal processingemployed in prior art oximeters by receiving input current signals fromat least two and preferably three light emitting devices of differentwavelengths and converting these input signals directly to digitalvoltage values, without first converting to analog voltages orseparating the signals. This is accomplished by using a chargedigitizing analog to digital converter with sufficient range torepresent the large DC signals and sufficient resolution to representthe small AC signals. This charge digitizing converter employs a currentintegrator as the front stage, which tends to average and filter inputnoise. This is an improvement over the analog current to voltageconversion used in traditional oximeters, which tend to amplify noise.

[0006] Once the input current is converted to a digital voltage value,all input signals are processed along the same digital hardware path,instead of the separate analog hardware paths required by thetraditional method. This system eliminates the need to match analoghardware components, and therefore further reduces potential errors.Furthermore, once the signals are digitized, a microprocessor canperform all of the signal processing, demultiplexing, and filteringsteps required by traditional oximeters. This reduction in the analogsignal processing stage increases both the speed and accuracy of theoximeter, decreases cost by eliminating expensive analog components, andreduces the size of the oximeter by eliminating physically large analogcomponents.

[0007] In another aspect of the invention, a method for analyzingoxygenation levels without the need for pulse detection and peak-valleymeasurements is also disclosed. The method comprises the steps ofstoring vectors of contiguous, paired infrared and red data samples overa period of time, using a least-squares minimization method fordetermining an infrared to red ratio, and determining a noise metric forfiltering noise from the resultant oxygenation calculations. The noisemetric substantially filters noise due to motion artifact, such assource: detector geometry variations and respiration noise, therebyproviding a more accurate oxygenation level reading.

[0008] In a further improvement, additional wavelengths can be added tothe oximeter to improve noise filtering or add medical monitoringfunctions to the oximeter. Because all signal conversion istime-multiplexed through a single analog to digital converter circuit, athird or further wavelengths can be easily and inexpensively added tothe sensor and device. The additional wavelengths can be used in anumber of applications which increase the accuracy of the oximeter orprovide additional monitoring functions, including: noise detection;dyshemoglobin detection and/or measurement; and indicator dyemeasurement.

[0009] Due to the ability of the digital circuitry of the presentinvention to process low level current input signals and to filter noisecomponents and the additional noise filtering functions disclosed, theoximeter can be used to accurately monitor oxygenation levels which werepreviously difficult to monitor, including fetal oxygenation levels andthe oxygenation levels of dark and thick skinned patients. In oneparticular embodiment the dynamic range of the analog to digitalconverter may be optimized to match the input signal range.

[0010] It is therefore an object of this invention to provide animproved method for non-invasively measuring fluid parameters.

[0011] It is another object of this invention to provide an improvedmethod for measuring arterial blood saturation.

[0012] It is another object of the invention to provide improved speedand accuracy in the measurements provided by oximeters.

[0013] It is another object of the invention to provide a direct analogto digital conversion of the input current signal with sufficient rangeto measure large DC signals and enough resolution to represent small ACsignals so that accurate measurements can be made with reduced analogsignal processing.

[0014] It is another object of the invention to provide a reduction inpotential errors by directly converting the input current signal to adigital voltage signal, thereby bypassing the current to voltageconversion step which can amplify noise.

[0015] It is another object of the invention to provide a reduction inpotential errors by processing all signals along one digital hardwarepath, thereby eliminating the need for matched analog components.

[0016] It is another object of the invention to provide an improvedoximeter having a reduced number of electronic circuit components.

[0017] It is still another object of the invention to provide areduction in the size of oximeters by eliminating physically largeanalog components.

[0018] It is yet a further object of the invention to provide animproved method and system for directly converting to digital signalform at least two signals from light emitting devices of differentwavelengths.

[0019] It is another object of the invention to provide an improvedmethod for filtering noise from oxygenation level calculations.

[0020] It is yet another object of the invention to provide a dynamicrange control for calculating oxygenation levels in a plurality ofsignal range levels.

[0021] It is still another object of the invention to provide animproved oximeter capable of monitoring a wide range of patients.

[0022] It is another object of the invention to provide a reduction inthe size and cost of detecting more than two wavelengths in oximeters.

[0023] These and other object and advantages of the invention, togetherwith the organization and manner of operation thereof, will becomeapparent from the following detailed description when taken inconjunction with the accompanying drawings described below.

BRIEF DESCRIPTION OF THE DRAWINGS

[0024]FIG. 1 illustrates a block diagram of the direct to digitaloximeter as connected to a sensor device; and

[0025]FIG. 2 illustrates the sensor device and direct to digitaloximeter connected to a patient.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

[0026] A block diagram of a direct to digital oximeter 10 constructed inaccordance with the invention, along with an external sensor device 20is shown in FIG. 1. The direct to digital oximeter 10 comprises a chargedigitizing analog to digital converter 30, a microprocessor 40, adigital to analog converter/LED driver 50, and a flash EPROM 60. Inorder to achieve sufficient accuracy, the charge digitizing analog todigital converter 30 preferably converts the input analog signal to adigital signal of at least 20 bits.

[0027] In a preferred embodiment (see FIG. 2) the sensor 20 is attachedto a blood-carrying tissue sample, such as the finger or ear lobe of apatient. Here, the sensor 20 is shown to consist of three light emittingdevices 70, 80, and 100 and a single photodetector 90, but the sensorcan include two or more light emitting devices of different wavelengthsand an associated plurality of photodetectors. Furthermore, althoughLEDs are commonly used in circuits of this type, the light emittingdevices can be laser diodes, white light sources, or other suitabledevices. To perform traditional pulse oximetry, however, the sensor 20comprises a red LED 70 and an infrared LED 80.

[0028] The LED's 70 and 80 are driven by digital signals from themicroprocessor 40. These digital signals are converted to analogvoltages by means of the digital to analog converter/LED driver 50.Light from the LED's 70 and 80 is transmitted through the tissue sample,and is detected by the photodetector 90, which produces an analogcurrent signal with an amplitude proportional to the amount of lightdetected in each bandwidth. The current signal from the photodetector 90is then digitized with 20 bits of resolution by the charge digitizinganalog to digital converter 30, and is sent to the microprocessor 40.Demultiplexing, ambient interference identification and elimination, andsignal filtering are performed by means of digital signal processingsoftware routines in the microprocessor 40. Once the signals areprocessed, the microprocessor 40 calculates the value of the ratio

(IR(AC)/IR(DC))(Red(AC)/Red(DC))

[0029] where the DC component represents the non-pulsating blood flow,and the AC component indicates the pulsatile blood flow. Themicroprocessor 40 then determines the absolute arterial oxygensaturation by comparing the result to the value stored in a look-uptable in flash EPROM 60.

[0030] In one preferred embodiment, the dynamic range of the analog todigital converter is optimized to match the input signal range, therebyproviding accurate monitoring over a wide range of input signals. Tooptimize the dynamic range, the output of the photodetector 90 isinitially read to determine the strength of the input signal. If thesignal is in a normal or high operating range, a dynamic range control62 (FIG. 2) is switched into the circuit to reduce the signal amplitude,preventing saturation of the analog to digital converter 30. The dynamicrange control 62 preferably comprises a current divider under softwarecontrol, and is inserted between the photodetector 90 and the analog todigital converter 30. The dynamic range control 62 reduces the currentinput level by a predetermined amount. In situations where thephotodetector 90 output is low (e.g., very dark skin, a thick tissuesite, and/or reflectance mode monitoring), the software detects the lowdigitized signal intensity and switches out the current divider,narrowing the dynamic range and effectively raising the signal gain.While one particular method of providing a dynamic range control isshown, it will be apparent to one of ordinary skill in the art that thedynamic range control could be provided in a number of ways includingamplifying a low signal to an expected higher level or reducing thecharge integration time of the charge digitizing converter, Furthermore,the dynamic range control may be implemented after current:voltageconversion for a voltage-input analog to digital converter.Additionally, either a fixed or variable reduction might be implementedin the dynamic range control.

[0031] In some applications, it is desirable to add at least oneadditional wavelength to the sensor 20 to improve the accuracy of theoximetry measurements or to provide additional medical monitoringfunctions to the oximeter 10. In this case, the light emitting device100 is added to the sensor 20, and related detector circuitry is addedto the photodector 90. Because all signal conversion is time-multiplexedthrough a single analog to digital converter circuit 30, the onlyadditional circuitry required to add a third or further wavelengths tothe oximeter 10 is a driver to drive the additional light emittingdevices of the sensor. Preferably, the light emitting devices 70, 80,and 100 are driven by a time-multiplexed digital to analog converter 50,controlled by a software-driven gate. However, it will be apparent toone of ordinary skill in the art that a pulse width modulated (PWM)output could also be used. The applications of the additionalwavelength(s) in the sensor 20 include, but are not limited to: noisedetection; dyshemoglobin detection and/or measurement; and indicator dyemeasurement.

[0032] A noise reference signal can facilitate the elimination of noisefrom a potentially compromised signal source. In pulse oximetry, thiscan be accomplished by tracking the absorbance of light at a wavelength(e.g., green) which is unaffected by the relative concentrations ofdifferent hemoglobin forms, which absorb primarily in the red. Theresultant signal is neutral in the absence of noise, but representsfluctuations in intensity due to changes in emitter:detector geometry orother noise sources. The noise reference signal can be employed in anumber of known mathematical approaches to noise elimination, includingadaptive signal processing.

[0033] Dyshemoglobins occur when the hemoglobin molecule binds withanother molecule besides oxygen, and include methemoglobins,sulfhemoglobins, and carboxyhemoglobins. A form which is of particularclinical significance is carboxyhemoglobin, the combination of carbonmonoxide with hemoglobin. Carbon monoxide poisoning is a significantcause of morbidity and mortality. Acute cases are often associated-withsmoke inhalation at the scene of a fire, but chronic poisoning, whereina patient presents with “flu” symptoms, may be more insidious.Conventional pulse oximeters cannot readily distinguishcarboxyhemoglobin from oxyhemoglobin, resulting in a falsely reassuringoxygen saturation reading. One approach which has been utilized (seeU.S. Pat. Nos. 4,167,331, 5,355,880, and 5,413,100, which are herebyincorporated in their entirety) requires a choice of wavelengths nearthree isobestic points (approximately 580, 650, and 800 nm). However, ifdetection without exact quantification is sufficient (e.g., to generatea warning), the addition of an 800 nm wavelength (isobestic betweenreduced and oxygenated hemoglobin) to the basic oximeter is sufficientto identify the presence of carboxyhemoglobin.

[0034] Indicator dyes are introduced as part of several monitoringprocedures, including dye dilution cardiac output assessment. Forexample, U.S. Pat. No. 5,494,031, which is hereby incorporated in itsentirety, discloses the use of indocyanine green dye for this purpose,with non-invasive concentration measurement utilizingphotoplethysmography. By adding a wavelength of substantially 800 nm tothe pulse oximeter sensor, along with known analysis software ormethods, and utilizing the infrared wavelength (940 nm) of the pulseoximeter sensor as a reference, a cardiac output assessment function isadded to a pulse oximeter.

[0035] Although the oximeter has been described employing threewavelengths, it will be apparent to one of ordinary skill in the artthat two or more of the noted features could be added simultaneously byadding additional light emitting devices and associated software to theoximeter.

[0036] In another embodiment of the invention, vectors of infrared andred signal data are stored and used by the microprocessor 40 todetermine the arterial oxygenation level. In this embodiment thearterial oxygenation levels are determined as a ratio of observed red acvalues (R^(obs) _(ac)) to observed infrared ac values (I^(obs) _(ac)). Anoise metric determined by comparing the observed red signal to apredicted red signal is employed to filter the noise components from thesignal, thereby obtaining a more accurate oxygenation reading.

[0037] Following are the steps used to determine the oxygenationsaturation level. Assuming for the moment ideal conditions,

I_(dc)=LP (I)

I_(ac)=I−I_(dc)

R_(dc)=LP (R)

[0038]  R_(ac)=R−R_(dc)

[0039]

[0040] where capital letters are employed to indicate vectors of Lcontiguous data samples (I={i₁, i₂, . . . , i_(L)}) equally spaced intime with an appropriate sampling rate. Vector length can impactstability of the I:R ratio calculation as well as ability to detectnoise in a timely and reliable fashion. The critical timing has beenshown experimentally to be the time to slew between minimum and maximumabsorbance (caused by the leading edge of the arterial blood bolus),only 100-200 msec in a hemodynamically effective pulse.

[0041] The ac subscripts indicate a high-passed or unbiasedpulsatile-component (variation in intensity), and the dc subscriptsindicate a low-passed, relatively long-term trend, or bias (the overallintensity level). Here LP() is assumed to have linear phase shift,permitting derivation of the high-passed signal by subtracting thelow-passed version from the original. This filtering may be accomplishedin hardware, but would be performed by software in the digital oximeter.

[0042] Given R and I, it is known to obtain the SpO₂ value by taking thescaled ratio of infrared and red pulse amplitudes, employing anempirically derived proportionality expressed here as an arbitraryfunction K:${SpO}_{2} = {K( \frac{( {{\max ( I_{ac} )} - {\min \quad ( I_{ac} )}} )/I_{dc}}{( {{\max ( R_{ac} )} - {\min ( R_{ac} )}} )/R_{dc}} )}$

[0043] where max() and min() denote the signal maxima and minima.

[0044] However, assuming equivalent LED:detector geometry, the I and Rvectors are linearly related. One vector, therefore, can be expressed asa simple linear combination (mX+b) of the other. The constant differenceis the difference in the low-passed intensity or dc levels, leaving thehigh-passed components linearly related by the I:R ratio ρ:

[0045]  R_(ac)=ρI_(ac)

[0046]

[0047] Then the formula for SpO₂ may be rewritten as $\begin{matrix}{{SpO}_{2} = {K( \frac{( {{\max ( I_{ac} )} - {\min \quad ( I_{ac} )}} )/I_{dc}}{( {{\max ( {\rho \quad I_{ac}} )} - {\min ( {\rho \quad I_{ac}} )}} )/R_{dc}} )}} \\{= {K( \frac{( {{\max ( I_{ac} )} - {\min \quad ( I_{ac} )}} )/I_{dc}}{{\rho ( {{\max( \quad I_{ac} )} - {\min( \quad I_{ac} )}} )}/R_{dc}} )}} \\{= {K( {( {R_{dc}/I_{dc}} )/\rho} )}}\end{matrix}$

[0048] The least-squares minimization (LSM) method is employed to derivep from the signal data by taking

ρ=(I_(ac)°R_(ac))/(I_(ac)°I_(ac))

[0049] where ° is used here to indicate the dot product of two vectors,yielding in this case the ratio of two scalars. (Note that it is assumedhere that the LP() function, although applied continuously over thedata, results in unbiased data vectors I_(ac) and R_(ac), since the LSMmethod actually specifies removal of the vector mean from the biaseddata prior to computation.) If this is not the case, it is possible torecast the calculation of ρ using (I−μ_(I)) and (R−μ_(R)) instead andstill derive the I:R ratio, assuming appropriate choice of vectorlength.)

[0050] This calculation of SpO₂ is independent of pulse location andpeak-valley measurements and will hereafter be called “continuous SpO₂calculation”. However, as will be described below, the calculation stillrelies upon the fact that pulsatile events takes place within the datavector extent.

[0051] The above calculations were determined under ideal conditions. Toobtain an accurate signal, therefore, it is necessary to account for thenoise encountered in pulse oximetry calculations. Under non-idealconditions, the observed intensities are actually

I^(obs)=I+N_(I)

R^(obs)=R +N_(R)

[0052] where N_(I) and N_(R) are noise components which are assumed tobe unbiased (low frequency interference tends not to effect therelatively short data vectors used. An observed I:R ratio ρ_(obs) isdefined by

R^(obs) _(ac)=ρ_(obs)I^(obs) _(ac)

[0053] where ρ_(obs)=ρ in the absence of noise. Now N_(I) and N_(R) maybe uncorrelated or correlated, and if the latter, may possess the sameor different proportionality ratio as the I:R ratio ρ of the desiredsignal components I and R. Considering the most difficult situation ofcorrelated noise, noise possessing the same ratio as ρ would not effectthe LSM calculation of ρ_(obs) from I^(obs) and R^(obs), giving ρ=ρobs.However, assuming a general case of

N_(R)=_(ρN)N_(I)

[0054] with ρN≠ρ, the noise components must be removed or canceled toaccurately calculate ρ_(obs) and thence SpO₂ directly from I_(obs) andR_(obs).

[0055] Since the SPO₂ value represents the binding state of millions ofhemoglobin molecules, as determined by relatively slow processes such asalveolar transport of molecular oxygen, pumping of blood through thecirculatory system, and venous return through the capillary beds, thepulse-to-pulse variation in the SpO₂ level is relatively small.

[0056] Motion artifact, however, tends to appear rather suddenly,induces non-linear effects on the sample-to-sample relationship betweenR^(obs) _(ac) and I ^(obs) _(ac), and disturbs the observed I:R ratio.Noise attributed to motion artifact, therefore, must be filtered toobtain an accurate calculation. The noise can be quantified with a noisemetric between R^(obs) _(ac) and the predicted red signal, obtained fromI^(obs) _(ac) by assuming a constant estimated _(ρest) (derived from therecent history of ρ_(obs) under low noise conditions):

R^(pred) _(ac)=ρest^(Iobs) _(ac)

[0057] Letting Δ() indicate a desired noise metric,

ν=Δ(R^(obs) _(ac), R^(pred) _(ac))/α

[0058] where α is a normalization factor (required if the metric is notinherently normalized). The metric is defined so that ν is zero only ifρ_(obs)=ρ, and otherwise is positive and increasing with increasingdisturbance of either or both observed intensity signals.

[0059] One distance metric is the average absolute difference betweencorresponding vector elements, or${\Delta \quad ( {V,W} )} = {( {\sum\limits_{j = 1}^{L}{{v_{j} - w_{j}}}} )/L}$

[0060] which is simple to compute and may be recursively obtained. Thismetric, however, requires a normalization for the expected magnitude ofthe signals. This normalization must be obtained from I^(obs) _(ac) andR^(obs) _(ac) data gathered under low noise conditions (denoted R^(est)_(ac) and I^(est) _(ac)). One example is the maximum magnitude of thetwo estimated signals, or$\alpha = {( {\sum\limits_{j = 1}^{L}{\max \quad ( {{r_{j}},{i_{j}}} )}} )/L}$

[0061] It will be apparent to one of ordinary skill in the art thatother distance metrics (including correlation) can be applied to theproblem of comparing R^(obs) _(ac) to R^(pred) _(ac).

[0062] By empirically establishing a threshold for acceptableperformance, the noise metric ν, calculated at the same time as the newρ_(obs), can be used to control not only SpO₂ averaging but other pulseoximetry processing (such as pulse rate determination).

[0063] As pointed out above, the continuous SpO2 calculation does notrequire determination of pulse timing. However, since it is desirable tolimit the vector length (e.g., to less than one second), it will bepossible in low heart rate situations to obtain data vectors containingno pulsatile event. These vectors will show less of the arterialabsorbance effect which is the basis of pulse oximetry. In preferredembodiments, therefore, an ECG or other indicator is used to synchronizethe data collection.

[0064] While preferred embodiments of the invention have been shown anddescribed, it will be clear to those skilled in the art that variouschanges and modifications can be made without departing from theinvention in its broader aspects as set forth in the claims providedhereinafter.

We claim:
 1. An oximeter for non-invasively measuring arterial oxygensaturation, comprising: a sensor including at least first, second andthird light emitting devices for producing light in at least threewavelengths; at least one photodetector for detecting said light, afterpassing through a tissue sample containing a pulsating blood supply, andfor producing an analog electrical current signal representing theabsorption of each wavelength of said light; an analog to digitalconverter for converting said analog electrical current signal to adigital voltage signal; and a processing unit for processing saiddigital voltage signal to calculate an arterial oxygen saturation. 2.The oximeter as defined in claim 1 , wherein the third wavelengthcomprises a wavelength which is unaffected by the relativeconcentrations of various hemoglobin forms.
 3. The oximeter of claim 1wherein the third wavelength provides a noise reference signal for usein detection and elimination of noise from the first and secondwavelengths.
 4. The oximeter of claim 1 wherein the third wavelengthprovides a signal for use in detection and/or measurement ofcarboxyhemoglobin concentration.
 5. The oximeter of claim 1 wherein thethird wavelength provides a signal for measuring indicator dyeconcentration.
 6. The oximeter of claim 1 wherein the third wavelengthis substantially in the range of 800 nm to provide a signal fornon-invasively measuring indocyanine green concentration.
 7. Theoximeter of claim 6 wherein the indocyanine green concentration measurednon-invasively with the third sensor wavelength is used to calculate thecardiac output.
 8. The oximeter as defined in claim 1 , wherein thelight emitting devices are LEDs.
 9. The oximeter as defined in claim 1 ,wherein the light emitting devices are laser diodes.
 10. An oximeter fornon-invasively measuring arterial oxygen saturation, comprising: asensor including at least first and second light emitting devices forproducing light in at least two wavelengths; at least one photodetectorfor detecting said light, after passing through a tissue samplecontaining a pulsating blood supply, and for producing an analogelectrical current signal representing the absorption of each wavelengthof said light; a dynamic range control for adjusting the range of theanalog electrical current signal to an expected input range; an analogto digital converter for converting said analog electrical currentsignal to a digital voltage signal; and a processing unit for processingsaid digital voltage signal to calculate an arterial oxygen saturation.11. The oximeter as defined in claim 10 , wherein the dynamic rangecontrol comprises a current divider.
 12. A method for non-invasivelymeasuring arterial oxygen saturation, comprising the steps of: producinglight of at least first, second, and third wavelengths; directing saidlight at a tissue sample containing a pulsating blood supply; detectingsaid light, after passing through said tissue sample, and producing ananalog electrical current signal representing the absorption rate ofeach wavelength of said light; then converting said analog electricalcurrent signal to a digital voltage signal; then processing the digitalvoltage signal to calculate an arterial oxygen saturation.
 13. Themethod as defined in claim 12 , further including the step of using atleast one wavelength as a noise reference signal for filtering noise.14. The method as defined in claim 12 , further including the step ofutilizing at least one wavelength to detect the presence ofcarboxyhemoglobin.
 15. The method as defined in claim 12 , furtherincluding the step of using at least one wavelength to provide a cardiacoutput assessment.
 16. The method as defined in claim 12 , furthercomprising the step of providing a dynamic range control for adjustingthe signal magnitude when outside of an expected input range.
 17. Amethod for calculating arterial oxygen saturation comprising thefollowing steps: producing light of at least first and secondwavelengths; directing said light at a tissue sample containing apulsating blood supply; detecting said light, after passing through saidtissue sample, and producing an analog electrical current signalrepresenting the absorption rate of each wavelength of said light; thenconverting said analog electrical current signal to a digital voltagesignal; filtering the digital voltage signal to provide a firstpulsatile signal representative of the pulsatile component of the lightabsorbed in the first wavelength and a second pulsatile signalrepresentative of the pulsatile component of the light absorbed in thesecond wavelength; sampling the digital voltage signal to provide afirst vector comprising data samples representative of light absorbed ofthe first wavelength; sampling the digital voltage signal to provide asecond vector comprising data samples representative of light absorbedof the second wavelength; calculating a ratio of the first vector to thesecond vector; and using the ratio to determine arterial oxygensaturation.
 18. The method as defined in claim 17 , further comprisingthe steps of comparing a predicted value of at least one of the firstand second wavelengths to an observed value of the same wavelength todetermine a noise metric.
 19. The method as defined in claim 18 ,further comprising the step of filtering data with the noise metric. 20.The method as defined in claim 18 , further comprising the step ofsynchronizing the calculation with a cardiac pulse detection signal. 21.The method as defined in claim 20 , in which the cardiac pulse detectionsignal is ECG.
 22. The method as defined in claim 18 , furthercomprising the step of using a least square minimization method tocalculate the ratio.